{"id":"W6885007213","doi":"10.13140/rg.2.2.20500.71047","title":"The Socio-Environmental Impacts of Public Urban Orchards: A Montreal Case-Study","year":2016,"lang":"en","type":"article","venue":"Open MIND","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Public transport; Urban planning; Public policy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005889494,0.0001101475,0.0001439427,0.000003175499,0.0003410754,0.0001275855,0.0004566853,0.00005192697,0.001200459],"category_scores_gemma":[0.00006682533,0.00002204712,0.00007386647,0.0001048664,0.0001390606,0.0002210817,0.0002654938,0.00005314597,0.00005311944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006707647,"about_ca_system_score_gemma":0.00001496986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001767147,"about_ca_topic_score_gemma":0.0085343,"domain_scores_codex":[0.9989144,0.0001830173,0.0002046042,0.0002484189,0.0001723207,0.0002771981],"domain_scores_gemma":[0.9993942,0.0002645767,0.00009694182,0.0001000488,0.00003091578,0.0001133096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002907642,0.0005028836,0.4067908,5.515703e-7,0.00003907741,0.0001134752,0.001398395,1.208876e-8,0.01736565,0.000006846368,0.002298574,0.5714547],"study_design_scores_gemma":[0.0005535079,0.0009963282,0.8302631,0.000005733647,0.00003075482,0.0001229779,0.08602589,9.216836e-7,0.0008095287,0.0001309697,0.08084086,0.0002193876],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959515,0.00009561662,1.614778e-7,0.001870809,0.00002738701,0.000601038,0.00006899496,0.000001751032,0.001382785],"genre_scores_gemma":[0.9972304,0.00001107808,0.00000657592,0.00001301003,0.00008187867,0.0000200384,0.000005751902,5.114368e-7,0.002630821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5712353,"threshold_uncertainty_score":0.9997126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03157012596967668,"score_gpt":0.2425571265646488,"score_spread":0.2109870005949722,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}